Infection Control & Hospital Epidemiology (2018), 39, 983–985 doi:10.1017/ice.2018.113
Concise Communication
Driving antimicrobial use improvement: attitudes of providers of adult hospital care on optimal attribution and feedback
Tara H. Lines PharmD1, Whitney J. Nesbitt PharmD, BCPS1 and George E. Nelson MD2 1Department of Pharmacy, Vanderbilt University Medical Center, Nashville, Tennessee and 2Department of Medicine, Division of Infectious Diseases, Vanderbilt University Medical Center, Nashville, Tennessee
Abstract
Understanding provider perceptions of antimicrobial use (AU) feedback is important for optimal implementation. A survey addressing AU attribution scenarios, feedback methods, and implementation barriers was distributed to inpatient providers. As AU scenarios became more complex, disagreement regarding AU attribution arose. All providers were highly concerned about barriers to AU reporting.
(Received 10 January 2018; accepted 25 April 2018; electronically published June 7, 2018)
Mandatory antimicrobial use (AU) reporting to National Healthcare Safety Network is anticipated and will provide national and local benchmarking. These data are currently reported at facility and unit levels and are not specific to service lines or providers.1,2 Resistance from providers may be encoun- tered given concerns that have been raised related to risk adjustment, data quality, and responsibility.3,4 Feedback of AU data to providers has been shown to reduce prescribing rates.5 Knowledge, attitudes, and practices (KAP) surveys have been used to assess provider perceptions of their own practice, antimicrobial stewardship principles, and AU appropriateness and may help identify and address barriers to providing feedback at a provider level.6–8 Few studies report the effects of providing quantitative AU data directly to providers or provider preference regarding AU feedback methodology.5,9,10 As institutions move toward providing AU feedback to providers, these behavioral concepts are important to understand provider attitudes better and increasing acceptance of a feedback program. In this study, we surveyed provider opinions and preferences relating to AU attribution, AU feedback methods, and barriers to assist in development of optimal AU feedback programs.
Methods
A 20-question survey approved by the Institutional Review Board at Vanderbilt University Hospital was e-mailed to adult inpatient providers in the following specialties: critical care (CC), emergency medicine (EM), infectious diseases (ID), medicine subspecialties (MED), and surgery (SG). Medicine subspecialties included
Author for correspondence: Tara H. Lines, Department of Pharmacy, Vanderbilt
University Medical Center, 1211 Medical Center Dr., VUH B-131, Nashville, TN 37232. E-mail:
Linesth@gmail.com,
George.nelson@
vanderbilt.edu PREVIOUS PRESENTATION: These data were presented at IDWeek 2017 on
October 6, 2017, in San Diego, California as a poster (no. 1426) Cite this article: Lines TH, et al. (2018). Driving antimicrobial use improvement:
attitudes of providers of adult hospital care on optimal attribution and feedback. Infection Control & Hospital Epidemiology 2018, 39, 983–985. doi: 10.10.1017/ice.2018.113
© 2018 by The Society for Healthcare Epidemiology of America. All rights reserved.
cardiology, endocrinology, gastroenterology, geriatrics, hematology/ oncology, hospitalists, nephrology, and rheumatology. The survey included demographic questions, a hypothetical patient hospitali- zation scenario addressing AU attribution, preferred feedback methods and barriers, and comparison metrics. The clinical sce- nario became progressively more complex in terms of number of consulting teams involved in the care of the patient and included transitions of care (Appendix A). Providers rated concern about AU feedback barriers on a scale of 1 (no concern) to 5 (very concerned). A small monetary incentive was offered for survey completion. The χ2 and Fisher exact tests were employed for categorical
variables, analysis of variance for mean comparison between groups, and Bonferroni correction for specific between group differences (α per test was <0.005 based on α per family of 0.05). For questions allowing multiple answers, each answer was analyzed separately and was not mutually exclusive.
Results
Of 766 providers who received the survey, 211 responded (27.5%). Most respondents were attending-level physicians (86.3%). The MED specialty was the most heavily represented among the responses (n=93; 44% of total), followed by SG (n=36; 17%), CC (n=30; 14%), ID (n=24; 11%), and EM (n=23; 11%). The CC and ID specialties had the highest response rates (64% and 60%, respectively), and SG had the lowest response rate (13%).
Antimicrobial use attribution questions
Most providers wanted their own institutions to determine attribution (89%) as opposed to external personnel. Specific survey questions and results are available in Appendix B. At the time of admission, 83% of providers attributed AU to the ED team, and 91% attributed AU to the ICU team at time of ICU transfer and subsequent therapy change. In the new ICU team scenario, 74% attributed AU to the new team even though they
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86 |
Page 87 |
Page 88 |
Page 89 |
Page 90 |
Page 91 |
Page 92 |
Page 93 |
Page 94 |
Page 95 |
Page 96 |
Page 97 |
Page 98 |
Page 99 |
Page 100 |
Page 101 |
Page 102 |
Page 103 |
Page 104 |
Page 105 |
Page 106 |
Page 107 |
Page 108 |
Page 109 |
Page 110 |
Page 111 |
Page 112 |
Page 113 |
Page 114 |
Page 115 |
Page 116 |
Page 117 |
Page 118 |
Page 119 |
Page 120 |
Page 121 |
Page 122 |
Page 123 |
Page 124 |
Page 125 |
Page 126 |
Page 127 |
Page 128 |
Page 129 |
Page 130 |
Page 131 |
Page 132 |
Page 133 |
Page 134 |
Page 135 |
Page 136 |
Page 137 |
Page 138 |
Page 139 |
Page 140
